Development and Validation of CCTA-based Radiomics Signature for Predicting Coronary Plaques With Rapid Progression

BACKGROUNDRapid plaque progression (RPP) is associated with a higher risk of acute coronary syndromes compared with gradual plaque progression. We aimed to develop and validate a coronary computed tomography angiography (CCTA)-based radiomics signature (RS) of plaques for predicting RPP. METHODSA to...

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Veröffentlicht in:Circulation. Cardiovascular imaging 2023-09, Vol.16 (9), p.e015340-e015340
Hauptverfasser: Chen, Qian, Xie, Guanghui, Tang, Chun Xiang, Yang, Liu, Xu, Pengpeng, Gao, Xiaofei, Lu, Mengjie, Fu, Yunlei, Huo, Yingsong, Zheng, Shaoqing, Tao, Xinwei, Xu, Hui, Yin, Xindao, Zhang, Long Jiang
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container_issue 9
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container_title Circulation. Cardiovascular imaging
container_volume 16
creator Chen, Qian
Xie, Guanghui
Tang, Chun Xiang
Yang, Liu
Xu, Pengpeng
Gao, Xiaofei
Lu, Mengjie
Fu, Yunlei
Huo, Yingsong
Zheng, Shaoqing
Tao, Xinwei
Xu, Hui
Yin, Xindao
Zhang, Long Jiang
description BACKGROUNDRapid plaque progression (RPP) is associated with a higher risk of acute coronary syndromes compared with gradual plaque progression. We aimed to develop and validate a coronary computed tomography angiography (CCTA)-based radiomics signature (RS) of plaques for predicting RPP. METHODSA total of 214 patients who underwent serial CCTA examinations from 2 tertiary hospitals (development group, 137 patients with 164 lesions; validation group, 77 patients with 101 lesions) were retrospectively enrolled. Conventional CCTA-defined morphological parameters (eg, high-risk plaque characteristics and plaque burden) and radiomics features of plaques were analyzed. RPP was defined as an annual progression of plaque burden ≥1.0% on lesion-level at follow-up CCTA. RS was built to predict RPP using XGBoost method. RESULTSRS significantly outperformed morphological parameters for predicting RPP in both the development group (area under the receiver operating characteristic curve, 0.82 versus 0.74; P=0.04) and validation group (area under the receiver operating characteristic curve, 0.81 versus 0.69; P=0.04). Multivariable analysis identified RS (odds ratio, 2.35 [95% CI, 1.32-4.46]; P=0.005) as an independent predictor of subsequent RPP in the validation group after adjustment of morphological confounders. Unlike unchanged RS in the non-RPP group, RS increased significantly in the RPP group at follow-up in the whole dataset (P
doi_str_mv 10.1161/CIRCIMAGING.123.015340
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We aimed to develop and validate a coronary computed tomography angiography (CCTA)-based radiomics signature (RS) of plaques for predicting RPP. METHODSA total of 214 patients who underwent serial CCTA examinations from 2 tertiary hospitals (development group, 137 patients with 164 lesions; validation group, 77 patients with 101 lesions) were retrospectively enrolled. Conventional CCTA-defined morphological parameters (eg, high-risk plaque characteristics and plaque burden) and radiomics features of plaques were analyzed. RPP was defined as an annual progression of plaque burden ≥1.0% on lesion-level at follow-up CCTA. RS was built to predict RPP using XGBoost method. RESULTSRS significantly outperformed morphological parameters for predicting RPP in both the development group (area under the receiver operating characteristic curve, 0.82 versus 0.74; P=0.04) and validation group (area under the receiver operating characteristic curve, 0.81 versus 0.69; P=0.04). Multivariable analysis identified RS (odds ratio, 2.35 [95% CI, 1.32-4.46]; P=0.005) as an independent predictor of subsequent RPP in the validation group after adjustment of morphological confounders. Unlike unchanged RS in the non-RPP group, RS increased significantly in the RPP group at follow-up in the whole dataset (P&lt;0.001). CONCLUSIONSThe proposed CCTA-based RS had a better discriminative value to identify plaques at risk of rapid progression compared with conventional morphological plaque parameters. These data suggest the promising utility of radiomics for predicting RPP in a low-risk group on CCTA.</description><identifier>ISSN: 1941-9651</identifier><identifier>EISSN: 1942-0080</identifier><identifier>DOI: 10.1161/CIRCIMAGING.123.015340</identifier><language>eng</language><ispartof>Circulation. Cardiovascular imaging, 2023-09, Vol.16 (9), p.e015340-e015340</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c288t-50cb094df8e7ef60ef8a88647b077aa3dc7f6617198b66c9be750d76a1ba62993</citedby><cites>FETCH-LOGICAL-c288t-50cb094df8e7ef60ef8a88647b077aa3dc7f6617198b66c9be750d76a1ba62993</cites><orcidid>0000-0001-6958-5201 ; 0000-0002-0564-8469 ; 0000-0001-7428-119X ; 0000-0003-4788-7668 ; 0000-0002-7238-2779 ; 0000-0002-6664-7224 ; 0000-0002-3224-6684</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,3686,27923,27924</link.rule.ids></links><search><creatorcontrib>Chen, Qian</creatorcontrib><creatorcontrib>Xie, Guanghui</creatorcontrib><creatorcontrib>Tang, Chun Xiang</creatorcontrib><creatorcontrib>Yang, Liu</creatorcontrib><creatorcontrib>Xu, Pengpeng</creatorcontrib><creatorcontrib>Gao, Xiaofei</creatorcontrib><creatorcontrib>Lu, Mengjie</creatorcontrib><creatorcontrib>Fu, Yunlei</creatorcontrib><creatorcontrib>Huo, Yingsong</creatorcontrib><creatorcontrib>Zheng, Shaoqing</creatorcontrib><creatorcontrib>Tao, Xinwei</creatorcontrib><creatorcontrib>Xu, Hui</creatorcontrib><creatorcontrib>Yin, Xindao</creatorcontrib><creatorcontrib>Zhang, Long Jiang</creatorcontrib><title>Development and Validation of CCTA-based Radiomics Signature for Predicting Coronary Plaques With Rapid Progression</title><title>Circulation. Cardiovascular imaging</title><description>BACKGROUNDRapid plaque progression (RPP) is associated with a higher risk of acute coronary syndromes compared with gradual plaque progression. We aimed to develop and validate a coronary computed tomography angiography (CCTA)-based radiomics signature (RS) of plaques for predicting RPP. METHODSA total of 214 patients who underwent serial CCTA examinations from 2 tertiary hospitals (development group, 137 patients with 164 lesions; validation group, 77 patients with 101 lesions) were retrospectively enrolled. Conventional CCTA-defined morphological parameters (eg, high-risk plaque characteristics and plaque burden) and radiomics features of plaques were analyzed. RPP was defined as an annual progression of plaque burden ≥1.0% on lesion-level at follow-up CCTA. RS was built to predict RPP using XGBoost method. RESULTSRS significantly outperformed morphological parameters for predicting RPP in both the development group (area under the receiver operating characteristic curve, 0.82 versus 0.74; P=0.04) and validation group (area under the receiver operating characteristic curve, 0.81 versus 0.69; P=0.04). Multivariable analysis identified RS (odds ratio, 2.35 [95% CI, 1.32-4.46]; P=0.005) as an independent predictor of subsequent RPP in the validation group after adjustment of morphological confounders. Unlike unchanged RS in the non-RPP group, RS increased significantly in the RPP group at follow-up in the whole dataset (P&lt;0.001). CONCLUSIONSThe proposed CCTA-based RS had a better discriminative value to identify plaques at risk of rapid progression compared with conventional morphological plaque parameters. These data suggest the promising utility of radiomics for predicting RPP in a low-risk group on CCTA.</description><issn>1941-9651</issn><issn>1942-0080</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNpNkMtOwzAQRS0EEqXwC8hLNil2HrazrAKUSAWqUmBpOfG4GCVxsFMk_p6UsmA1szj3auYgdEnJjFJGr4tyXZQP80X5uJjROJkRmiUpOUITmqdxRIggx787jXKW0VN0FsIHISwhmZigcANf0Li-hW7AqtP4VTVWq8G6DjuDi2IzjyoVQOO10ta1tg742W47New8YOM8XnnQth5st8WF865T_huvGvW5g4Df7PA-BnurR8xtPYQwFp-jE6OaABd_c4pe7m43xX20fFqUxXwZ1bEQQ5SRuiJ5qo0ADoYRMEIJwVJeEc6VSnTNDWOU01xUjNV5BTwjmjNFK8XiPE-m6OrQ23u3P2eQrQ01NI3qwO2CjAVjnNGMpiPKDmjtXQgejOy9bcdXJCVyb1n-syxHy_JgOfkBT_lyjw</recordid><startdate>202309</startdate><enddate>202309</enddate><creator>Chen, Qian</creator><creator>Xie, Guanghui</creator><creator>Tang, Chun Xiang</creator><creator>Yang, Liu</creator><creator>Xu, Pengpeng</creator><creator>Gao, Xiaofei</creator><creator>Lu, Mengjie</creator><creator>Fu, Yunlei</creator><creator>Huo, Yingsong</creator><creator>Zheng, Shaoqing</creator><creator>Tao, Xinwei</creator><creator>Xu, Hui</creator><creator>Yin, Xindao</creator><creator>Zhang, Long Jiang</creator><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-6958-5201</orcidid><orcidid>https://orcid.org/0000-0002-0564-8469</orcidid><orcidid>https://orcid.org/0000-0001-7428-119X</orcidid><orcidid>https://orcid.org/0000-0003-4788-7668</orcidid><orcidid>https://orcid.org/0000-0002-7238-2779</orcidid><orcidid>https://orcid.org/0000-0002-6664-7224</orcidid><orcidid>https://orcid.org/0000-0002-3224-6684</orcidid></search><sort><creationdate>202309</creationdate><title>Development and Validation of CCTA-based Radiomics Signature for Predicting Coronary Plaques With Rapid Progression</title><author>Chen, Qian ; Xie, Guanghui ; Tang, Chun Xiang ; Yang, Liu ; Xu, Pengpeng ; Gao, Xiaofei ; Lu, Mengjie ; Fu, Yunlei ; Huo, Yingsong ; Zheng, Shaoqing ; Tao, Xinwei ; Xu, Hui ; Yin, Xindao ; Zhang, Long Jiang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c288t-50cb094df8e7ef60ef8a88647b077aa3dc7f6617198b66c9be750d76a1ba62993</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chen, Qian</creatorcontrib><creatorcontrib>Xie, Guanghui</creatorcontrib><creatorcontrib>Tang, Chun Xiang</creatorcontrib><creatorcontrib>Yang, Liu</creatorcontrib><creatorcontrib>Xu, Pengpeng</creatorcontrib><creatorcontrib>Gao, Xiaofei</creatorcontrib><creatorcontrib>Lu, Mengjie</creatorcontrib><creatorcontrib>Fu, Yunlei</creatorcontrib><creatorcontrib>Huo, Yingsong</creatorcontrib><creatorcontrib>Zheng, Shaoqing</creatorcontrib><creatorcontrib>Tao, Xinwei</creatorcontrib><creatorcontrib>Xu, Hui</creatorcontrib><creatorcontrib>Yin, Xindao</creatorcontrib><creatorcontrib>Zhang, Long Jiang</creatorcontrib><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Circulation. Cardiovascular imaging</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chen, Qian</au><au>Xie, Guanghui</au><au>Tang, Chun Xiang</au><au>Yang, Liu</au><au>Xu, Pengpeng</au><au>Gao, Xiaofei</au><au>Lu, Mengjie</au><au>Fu, Yunlei</au><au>Huo, Yingsong</au><au>Zheng, Shaoqing</au><au>Tao, Xinwei</au><au>Xu, Hui</au><au>Yin, Xindao</au><au>Zhang, Long Jiang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Development and Validation of CCTA-based Radiomics Signature for Predicting Coronary Plaques With Rapid Progression</atitle><jtitle>Circulation. Cardiovascular imaging</jtitle><date>2023-09</date><risdate>2023</risdate><volume>16</volume><issue>9</issue><spage>e015340</spage><epage>e015340</epage><pages>e015340-e015340</pages><issn>1941-9651</issn><eissn>1942-0080</eissn><abstract>BACKGROUNDRapid plaque progression (RPP) is associated with a higher risk of acute coronary syndromes compared with gradual plaque progression. We aimed to develop and validate a coronary computed tomography angiography (CCTA)-based radiomics signature (RS) of plaques for predicting RPP. METHODSA total of 214 patients who underwent serial CCTA examinations from 2 tertiary hospitals (development group, 137 patients with 164 lesions; validation group, 77 patients with 101 lesions) were retrospectively enrolled. Conventional CCTA-defined morphological parameters (eg, high-risk plaque characteristics and plaque burden) and radiomics features of plaques were analyzed. RPP was defined as an annual progression of plaque burden ≥1.0% on lesion-level at follow-up CCTA. RS was built to predict RPP using XGBoost method. RESULTSRS significantly outperformed morphological parameters for predicting RPP in both the development group (area under the receiver operating characteristic curve, 0.82 versus 0.74; P=0.04) and validation group (area under the receiver operating characteristic curve, 0.81 versus 0.69; P=0.04). Multivariable analysis identified RS (odds ratio, 2.35 [95% CI, 1.32-4.46]; P=0.005) as an independent predictor of subsequent RPP in the validation group after adjustment of morphological confounders. Unlike unchanged RS in the non-RPP group, RS increased significantly in the RPP group at follow-up in the whole dataset (P&lt;0.001). CONCLUSIONSThe proposed CCTA-based RS had a better discriminative value to identify plaques at risk of rapid progression compared with conventional morphological plaque parameters. These data suggest the promising utility of radiomics for predicting RPP in a low-risk group on CCTA.</abstract><doi>10.1161/CIRCIMAGING.123.015340</doi><orcidid>https://orcid.org/0000-0001-6958-5201</orcidid><orcidid>https://orcid.org/0000-0002-0564-8469</orcidid><orcidid>https://orcid.org/0000-0001-7428-119X</orcidid><orcidid>https://orcid.org/0000-0003-4788-7668</orcidid><orcidid>https://orcid.org/0000-0002-7238-2779</orcidid><orcidid>https://orcid.org/0000-0002-6664-7224</orcidid><orcidid>https://orcid.org/0000-0002-3224-6684</orcidid></addata></record>
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title Development and Validation of CCTA-based Radiomics Signature for Predicting Coronary Plaques With Rapid Progression
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